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Bertrand Vernay (Intervention)
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DOI : 10.60527/4e91-g889
Citer cette ressource :
Bertrand Vernay. RTmfm. (2021, 16 mars). Les outils machine/deep learning open source pour plateforme de microscopie. [Vidéo]. Canal-U. https://doi.org/10.60527/4e91-g889. (Consultée le 2 juin 2024)

Les outils machine/deep learning open source pour plateforme de microscopie

Réalisation : 16 mars 2021 - Mise en ligne : 16 juin 2021
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Descriptif

Présentation Bertrand Vernay

UMR7104 IGBMC, Institut de génétiques et de biologie moléculaire et cellulaire

Université de Strasbourg Illkirch 

Intervention
Thème
Documentation

1-    Machine learning

 

Machine learning for bio-image analysis Robert Haase 08a Machine Learning for Pixel and Object Classification https://www.youtube.com/watch?v=dstjhCPBDOY&list=PL5ESQNfM5lc7SAMstEu082ivW4BDMvd0U&index=19

Robert Haase 08b Machine Learning for Pixel Classification in Fiji https://www.youtube.com/watch?v=TfS7ncUaOq4&list=PL5ESQNfM5lc7SAMstEu082ivW4BDMvd0U&index=20

Robert Haase 08c Machine Learning for Pixel and Object Classification in ilastik https://www.youtube.com/watch?v=35ykpzsUDRE&list=PL5ESQNfM5lc7SAMstEu082ivW4BDMvd0U&index=21

Trainable Weka Segmentation (https://imagej.net/Trainable_Weka_Segmentation)

ilastik (https://www.ilastik.org/)

Webinaire #1: ilastik beyond pixel classification - [NEUBIASAcademy@Home] Webinar https://www.youtube.com/watch?v=_ValtSLeAr0&t=0s

QuPath (https://qupath.github.io/)

Webinaire #1: Quantitative Pathology & BioImage Analysis: QuPath - [NEUBIASAcademy@Home]

Webinar https://www.youtube.com/watch?v=4An5n6Y_rRI&t=0s

 

2-    deep learning

StarDist ( https://github.com/stardist/stardist )

Introduction to nuclei segmentation with StarDist - [NEUBIASAcademy@Home] Webinar https://www.youtube.com/watch?v=Amn_eHRGX5M

CellPose ( https://www.cellpose.org/ )

Webinaire #1: Cellpose: a generalist algorithm for cellular segmentation https://www.youtube.com/watch?v=7y9d4VIKiS8

 Webinaire #2: Using Deep Learning for Cellular Segmentation by Carsen Stringer https://www.youtube.com/watch?v=4ZZjr6SFBV8

DeepImageJ ( https://deepimagej.github.io/deepimagej/about.html )

Webinaire #1: Intro to Machine Learning-DeepLearning-DeepimageJ - [NEUBIASAcademy@Home]

Webinar https://www.youtube.com/watch?v=0vTbsO8Vnuo  

ZerocostDL4Mic ( https://github.com/HenriquesLab/ZeroCostDL4Mic )

Webinaire #1: Romain Laine - ZeroCostDL4Mic: state-of-the-art deep learning for microscopy, made hassle-free https://www.youtube.com/watch?v=JxzflpmjMm4  Webinaire #2: I2K 2020 tutorial: Deep learning assisted image analysis using ZeroCostDL4Mic https://www.youtube.com/watch?v=A7yyAhT12mQ

3-    Outils d'annotation

Labkit ( https://imagej.net/Labkit )

labelImg ( https://github.com/tzutalin/labelImg )

itk-SNAP ( http://www.itksnap.org/pmwiki/pmwiki.php )

makesense.ai ( https://www.makesense.ai/ )

discussion sur les outils d'annotation sur le forum image.sc https://forum.image.sc/t/comparaison-of-some-tools-for-3d-dense-ground-truth-annotations/38918  

4 - Dépôts de données

NEUBIAS Zenodo https://zenodo.org/communities/neubias/?page=1&size=20  Bioimage Model Zoo ( https://bioimage.io/#/ )

Image Data Resource( https://idr.openmicroscopy.org/ ) https://bioimage.io/#/

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